Restraining system comprising a restraining device for protecting at least one passenger and a method for controlling a restraining system

ABSTRACT

A restraint system having a restraint device for protecting at least one passenger and a method for controlling a restraint system are proposed, which act so as to transform using a wavelet transformation, a signal measured by an acceleration sensor into a frequency range and in order to determine from the transformed signal the optimal triggering time point for the restraint device. For this purpose, the wavelet-transformed signal, on the one hand, is used for determining features in order to determine a crash type, and, on the other hand, to determine the braking acceleration energy. If the braking acceleration energy lies above a preestablished threshold value and if the identified crash type requires a triggering of the restraint system, then the restraint system is triggered.

BACKGROUND INFORMATION

[0001] The present invention relates to a restraint system having arestraint device for protecting at least one passenger, and to a methodfor controlling a restraint system, in accordance with the speciesdefined in the independent claims.

[0002] From the Laid-Open Print DE 197 13 087 A1, a vehicle passengerrestraint system is known which has an acceleration sensor for measuringthe acceleration of the motor vehicle, an analog/digital converter fordigitalizing the output signals of the acceleration sensor, a wavelettransformer for transforming the digital signals in order to generatewavelet coefficients, and a device for calculating the speed, anactuator for the restraint system being activated as soon as the changein speed and the wavelet coefficient each exceed preestablishedthreshold values.

[0003] The wavelet coefficient is calculated using a wavelet functionwhich was generated from a master wavelet function using a scalingfactor and a displacement parameter for the time shift.

SUMMARY OF THE INVENTION

[0004] In contrast, the restraint system according to the presentinvention having a restraint device for protecting at least onepassenger, and the method according to the present invention forcontrolling a restraint system, having the features of the independentpatent claims, have the advantage that as a result of distinguishingbetween crash types and by evaluating the braking acceleration energy,an optimal triggering time point is determined for the restraint system.As a result, the triggering of the restraint system is moresituation-appropriate.

[0005] As a result of the measures and refinements indicated in thedependent claims, advantageous improvements of the restraint systemindicated in the independent claims and of the method for controlling arestraint system are possible.

[0006] It is particularly advantageous that the crash types aredetermined on the basis of extracted features, using a comparison ofrecords of learned and stored features. In this way, an unambiguousidentification of the specific crash type is possible, so as to decidewhether the restraint system should be triggered or not. Not every crashcalls for the triggering of the restraint system. Among such are, forexample, front-end crashes having a velocity of maximum 15 km/h or arear-end crash. In addition, spurious signals are identified in this wayand therefore advantageously do not lead to a triggering of therestraint device.

[0007] In addition, it is advantageous that between the learned featuresand the extracted features differences are calculated, and thesedifferences are compared to a preestablished threshold value, so that anidentification of a crash type only takes place when a threshold valueis not exceeded. In other words, only then is the difference so smallthat one can speak of an identification of this feature.

[0008] It is also advantageous that the measure for the brakingacceleration energy is also compared to a second threshold value, sothat the triggering actually takes place only if the crash type requiresa triggering and if the measure lies above the threshold value, so thata triggering is therefore necessary. Both conditions must therefore befulfilled in order to generate a triggering. In this way,advantageously, spurious triggerings become less likely, and thereforetriggering a restraint device becomes more reliable.

DRAWING

[0009] Exemplary embodiments of the present invention are depicted inthe drawing and are discussed in greater detail in the descriptionbelow.

[0010]FIG. 1 depicts as a block diagram the restraint system accordingto the present invention, and

[0011]FIG. 2 depicts as a flow chart the method according to the presentinvention for controlling a restraint system.

DESCRIPTION

[0012] As a result of the increasing use of restraint systems such asairbags and belt tighteners in motor vehicles, it is of decisiveimportance to determine the time point at which restraint systems ofthis type should be triggered. In this context, the type of collisionbetween vehicles or obstacles and the velocity with which it takes placeare of decisive importance for the triggering time point.

[0013] Wavelets have been determined to be a popular and successfulmethod in the area of signal analysis, the wavelet transformationfinding application in varied areas. The wavelet transformation is amethod for subdividing an input signal into so-called wavelets as itscomponents and for reuniting the original input signal as a linearsuperimposition of the wavelets. The wavelet transformation is appliedeffectively for analyzing an unstable or inconstant state, for example,in a state transition. Acting as the base is a master wavelet function,using which a scaling transformation and a Fourier transformation arecarried out. The master wavelet function is a quadratically integrablefunction, which is temporally localized, or it is a function in the timerange, although the base must be that which is limited and that which,in a distance range, is rapidly dampened or weakened. In the wavelettransformation, the subdivision rate for the analysis can be freelyselected. In comparison to the Fourier transformation, base functionssuch as wavelets that occupy several intervals both in the time as wellas in the frequency range are better suited for irregularities. On thebasis of the locality of the functions, even particularly steep edges offunctions can be optimally depicted.

[0014] Presented according to the present invention are, therefore, arestraint system having a restraint device and a method for controllinga restraint system, the system operating using a wavelet transformationand determining features on the basis of the wavelet-transformedsignals, comparing these features to stored and learned features, inorder to determine a crash type, on the basis of the transformed waveletsignal, determining the acceleration energy or at least a measure forit, and, on the basis of the crash type and of the measure for theacceleration energy, deciding whether the restraint device of therestraint system should be triggered or not.

[0015] In FIG. 1, the restraint system according to the presentinvention is depicted as a block diagram. An acceleration sensor 1 isconnected to an input of an analog/digital converter 2. The data outputof analog/digital converter 2 leads to a data input of a processor 3.Processor 3 is connected via a data input/output to a memory 4. A dataoutput of processor 3 leads to an actuator 5, whose output in turn isconnected to restraint device 6.

[0016] Acceleration sensor 1 measures the acceleration of the vehicle inwhich the restraint system according to the present invention islocated. Acceleration sensor 1 is arranged at a specific location in thevehicle, for example, in a central section, so that acceleration sensor1 outputs a signal as a function of an acceleration or a deceleration,as a negative acceleration. Different sensor types can be used foracceleration sensor 1, such as a sensor of a mechanical construction,which uses a mass rotor, a sensor that is made of a semiconductor,semiconductor sensors preferably having membranes, and a sensor can beused which, in the event that a vehicle collision occurs, only outputs asignal in case the deceleration of the vehicle attains the value whichcorresponds to a collision force greater than a preestablished measure.A forward acceleration and a deceleration as the output signals ofacceleration sensor 1 can easily be distinguished on the basis of a plusor minus sign. The output signal of acceleration sensor 1 then leads tothe input of analog/digital converter 2, which digitizes these outputsignals and then feeds them to processor 3. Processor 3 controlsactuator 5, which has a firing control circuit, to trigger restraintsystem 6, if called for. Processor 3 is a conventional processor, forexample, a microcontroller, which uses memory 4, on the one hand, tostore intermediate results and, on the other hand, to use the storeddata to make a crash type identification. Processor 3 also carries outthe wavelet transformation of the data measured by acceleration sensor1. The wavelet transformation has the advantage that a signal can besubdivided into its frequency components at a constant relativebandwidth without loss of time information. The wavelet transformationis especially suitable for non-steady signals and is provided with veryrapid algorithms, which can be realized using filter bank structures.For this purpose, hardware can be used that is provided only for thispurpose.

[0017] Mathematically, the wavelet transformation can be described as anintegral transformation of the signal into orthogonal subspaces. Thewavelet coefficients calculated in this context are essentiallydetermined by two parameters. One is the scaling factor, the other isthe time displacement. In addition, in the wavelet transformation, afunction is used in accordance with which the signal is transformed, andthis function is especially dependent on these two parameters, thescaling factor and the time displacement.

[0018] If the wavelet transformation is applied to crash accelerationsignals, information can be extracted as a result concerning the maximumsignal energies as well as concerning average signal energies indifferent frequency bands of the signal. These are characteristicinformation bits for the individual crash type and in combination theycan be used for classifying or recognizing these crash types. Therefore,two features are present per frequency band. Using these features, it isthen possible to identify the individual crash types. Here, sevendifferent crash types are distinguished, for each crash type a record ofstored and learned features being available. The features determined byacceleration sensor 1 are compared with these stored features,differences in this context between the measured and the stored featuresbeing calculated, i.e., energy differences being calculated. Thesedifferences must lie below a preestablished threshold value in order toidentify a crash type. In other words, all the features of a record fora crash must have a difference below this first threshold value. Onlythen is the specific crash type identified. The crash types are createdso that an identification is always made possible, at least one crashtype representing a non-triggering-event, i.e., crash types which do notresult in the triggering of restraint device 6.

[0019] The following table, the seven different crash types aredepicted. Alternatively, it is possible that more or fewer crash typescan be provided for. No. Designation Description 1 SEVERE Very fastcrashes against a hard barrier (e.g., 50 km/h frontal) 2 LIGHT Hardcrashes of moderate speed (e.g., 20-30 km/h frontal) 3 OHARD Hard,relatively fast offset and other non-frontal crashes (e.g., 55 km/hoffset 50% left, 48 km/h pole collision 100%, 65 km/h ODB 40% right) 4OSOFT Soft offset and other non-frontal crashes of fast to moderatespeed (e.g., 60 km/h ODB ADAC 40% left, 25 km/h 30° diagonal right) 5NON Non-triggering crashes (e.g., 15 km/h frontal and damage types) 6MIS Misuse tests (non-triggering) 7 REAR-END Rear-end crashes(non-triggering)

[0020] Processor 3, in addition to classifying the crash on the basis ofthe measured features, also carries out the calculation of the brakingacceleration energy and compares this braking acceleration energy to asecond preestablished threshold value, it being necessary that thebraking acceleration energy lie above this threshold in order to be ableto transmit a triggering signal for restraint device 6. The thresholdvalue is specific for the detected crash type, and there are as manythreshold values as there are crash types that result in the triggeringof the restraint system.

[0021] This condition for the braking acceleration energy is thereforeonly checked if a specifically identified crash type results in theconsequence that a triggering signal is transmitted for restraint device6. In crash types 1 through 4, a triggering signal is transmitted,whereas in crash types 5 through 7, it is omitted. Therefore, if thebraking acceleration energy lies above the threshold value and one ofcrash types 5 through 7 is identified, then no triggering signal resultsfor restraint device 6, because one of the conditions has not beenfulfilled. Rather, both conditions must be fulfilled in order to give atriggering signal for restraint device 6. If a triggering signal of thistype is detected by processor 3 as one to be transmitted, then processor3 transmits this fact to actuator 5, which then triggers restraintdevice 6 using a control signal.

[0022] In FIG. 2, the method according to the present invention forcontrolling a restraint system is depicted as a flow chart. In methodstep 7, the acceleration of the vehicle is measured by accelerationsensor 1. In method step 8, the analog/digital conversion of the signalsgenerated by acceleration sensor 1 takes place. In method step 9, thedigitalized signals are subjected to the wavelet transformation totransform them into the frequency space. In method step 10, the signalsare subdivided into frequency bands, and for each frequency band theaverage and the maximum signal energies are calculated. In method step11, an identification of the specific crash type is carried out on thebasis of the average and the maximum signal energies per frequency band,as the extracted features, and on the basis of the stored features,which are stored as records in each case for the preestablished crashtypes. This identification, as was mentioned above, is carried out bycalculating the difference between the measured features and the storedfeatures. In method step 13, a check test is carried out as to whetherthe identified crash type has the consequence of triggering restraintdevice 6. If such is not the case, then in method step 14 the methodaccording to the present invention is terminated.

[0023] After method step 13, in method step 12, a measure for thebraking acceleration energy is calculated from the same wavelettransformed signals, the low-frequency portion of the signal energybeing especially considered. In method step 15, this measure for thebraking acceleration energy is compared with a preestablished thresholdvalue which is characteristic for the crash type detected in method step11. If the braking acceleration energy lies above the specific thresholdvalue and if a crash type is detected which results in the triggering ofrestraint device 6, then in method step 16 restraint device 6 istriggered by actuator 5, because at method step 16 only those crashtypes arrive which result in the triggering of restraint device 6.Therefore, the AND-operation takes place here. If in method step 15 itwas determined that the braking acceleration energy lies below thepreestablished threshold value, then in method step 17, restraint device6 is not triggered.

What is claimed is:
 1. A restraint system having a restraint device forprotecting at least one passenger, the restraint system having anacceleration sensor (1) for measuring an acceleration of the vehicle, ananalog/digital converter (2) for converting an output signal of theacceleration sensor (1) into a digital signal corresponding to theacceleration, a processor (3) for carrying out a wavelet transformationof the digital signal into a frequency signal, a memory (4), and anactuator (5) for controlling the restraint device (6), wherein theprocessor (3) subdivides the frequency signal into individual frequencyranges, the processor (3), for each frequency range measures thespecific maximum and the specific average signal energy in order toextract features; the processor (3) determines a crash type on the basisof the features, the processor (3) determines from the frequency signala measure for the braking acceleration energy; and the processor (3), asa function of the measure and of the crash type, transmits a controlsignal to the actuator (5).
 2. The restraint system as recited in claim1, wherein the processor (3) compares the extracted features to thefeatures that are learned and stored in the memory (4), in order todetermine the crash type, the learned features being subdivided intorecords, and crash types being assigned in each case to the records. 3.The restraint system as recited in claim 2, wherein the processor (3)calculates differences between the extracted features and the records ofthe stored features, and, if the differences of one record lie beneath afirst threshold value, the processor (3) assigns the extracted featuresto the crash type of this record.
 4. The restraint system as recited inclaim 3, wherein the processor (3) compares the measure to a secondthreshold value that is changeable over time and, if the measure liesabove the second threshold value, the processor (3) transmits to theactuator (5) a control signal as a function of the identified crashtype.
 5. A method for controlling a restraint system (6), theacceleration of a vehicle being measured as an acceleration signal, theacceleration signal being digitalized into a digital signal, the digitalsignal being transformed using a wavelet transformation into a frequencysignal, the restraint system (6) being controlled by an actuator (5),wherein the frequency signal is subdivided into frequency ranges, thespecific maximum and specific average signal energies are determined foreach frequency range in order to extract features; the crash type isdetermined on the basis of the features; a measure for the brakingacceleration energy is determined from the frequency signal; and acontrol signal is transmitted to the actuator (5) as a function of themeasure and of the crash type.
 6. The method as recited in claim 5,wherein the processor (3) compares the extracted features to the storedfeatures in order to determine the crash type, the stored features beingsubdivided into records, and the specific crash types being assigned tothe records.
 7. The method as recited in claim 6, wherein the processor(3) calculates differences between the extracted features and therecords of the stored features, and, if the differences for one recordlie below a first threshold value, the processor (3) assigns theextracted features to the crash type of this record.
 8. The method asrecited in claim 5, 6, or 7, wherein the processor (3) compares themeasure to a second threshold value, and if the measure lies above thesecond threshold value, the processor (3) transmits a triggering signalto the actuator (5).